CN105675838B - A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods - Google Patents
A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods Download PDFInfo
- Publication number
- CN105675838B CN105675838B CN201610237451.6A CN201610237451A CN105675838B CN 105675838 B CN105675838 B CN 105675838B CN 201610237451 A CN201610237451 A CN 201610237451A CN 105675838 B CN105675838 B CN 105675838B
- Authority
- CN
- China
- Prior art keywords
- mrow
- water outlet
- total phosphorus
- outlet total
- msub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 101
- 229910052698 phosphorus Inorganic materials 0.000 title claims abstract description 91
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 title claims abstract description 89
- 239000011574 phosphorus Substances 0.000 title claims abstract description 89
- 238000000034 method Methods 0.000 title claims abstract description 52
- 239000010865 sewage Substances 0.000 claims abstract description 44
- 230000008569 process Effects 0.000 claims abstract description 34
- 238000005259 measurement Methods 0.000 claims abstract description 20
- 238000012360 testing method Methods 0.000 claims abstract description 9
- 239000011159 matrix material Substances 0.000 claims description 14
- 238000013500 data storage Methods 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 4
- 229910052760 oxygen Inorganic materials 0.000 claims description 4
- 239000001301 oxygen Substances 0.000 claims description 4
- 230000009467 reduction Effects 0.000 claims description 4
- 239000007787 solid Substances 0.000 claims description 4
- 238000005273 aeration Methods 0.000 claims description 3
- 230000001419 dependent effect Effects 0.000 claims description 3
- 238000004062 sedimentation Methods 0.000 claims description 3
- 239000000725 suspension Substances 0.000 claims description 3
- 238000013519 translation Methods 0.000 claims description 3
- 238000011068 loading method Methods 0.000 claims description 2
- 238000012216 screening Methods 0.000 claims 1
- 238000005516 engineering process Methods 0.000 abstract description 15
- 238000013461 design Methods 0.000 abstract description 8
- 238000004891 communication Methods 0.000 abstract description 5
- 230000008859 change Effects 0.000 abstract description 4
- 239000002351 wastewater Substances 0.000 abstract description 2
- 238000004458 analytical method Methods 0.000 description 13
- 238000011160 research Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 5
- 238000012546 transfer Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000011897 real-time detection Methods 0.000 description 3
- 239000000523 sample Substances 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000005538 encapsulation Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 239000013505 freshwater Substances 0.000 description 2
- JEGUKCSWCFPDGT-UHFFFAOYSA-N h2o hydrate Chemical compound O.O JEGUKCSWCFPDGT-UHFFFAOYSA-N 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000007935 neutral effect Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- FDWIKIIKBRJSHK-UHFFFAOYSA-N 2-(2-methyl-4-oxochromen-5-yl)acetic acid Chemical compound C1=CC=C2OC(C)=CC(=O)C2=C1CC(O)=O FDWIKIIKBRJSHK-UHFFFAOYSA-N 0.000 description 1
- 102000010637 Aquaporins Human genes 0.000 description 1
- 108010063290 Aquaporins Proteins 0.000 description 1
- 101100436077 Caenorhabditis elegans asm-1 gene Proteins 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 101100204282 Neurospora crassa (strain ATCC 24698 / 74-OR23-1A / CBS 708.71 / DSM 1257 / FGSC 987) Asm-1 gene Proteins 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000012851 eutrophication Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000005416 organic matter Substances 0.000 description 1
- 238000004540 process dynamic Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004064 recycling Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000004065 wastewater treatment Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
- G01N33/182—Specific anions in water
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Biochemistry (AREA)
- Analytical Chemistry (AREA)
- Medicinal Chemistry (AREA)
- Immunology (AREA)
- Food Science & Technology (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Purification Treatments By Anaerobic Or Anaerobic And Aerobic Bacteria Or Animals (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods belong to sewage disposal water quality parameter on-line checking field, the relation of water outlet total phosphorus and other process variables is analysed in depth from sewage disposal process magnanimity service data, the intelligent characteristic modeling method of water outlet total phosphorus in sewage disposal process is proposed first, obtains the 5 classes process variable strong with water outlet total phosphorus correlation.Meanwhile the hardware platform of intelligent checking system has been built based on functional requirement design cycle and waste water processes technological design, further accurate each change measurement current potential.In addition, water outlet total phosphorus intelligent Computation Technology is embedded in intelligent checking system software, complete software and hardware communication channel is built, water outlet total phosphorus intelligent checking system hardware platform, operation software and water outlet total phosphorus intelligent Computation Technology are integrated, complete water outlet total phosphorus intelligent checking system is formed, compensate for the blank both at home and abroad on water outlet total phosphorus intelligent testing technology application.
Description
Technical field
The invention belongs to sewage disposal water quality parameter on-line checking field, on the basis of the true service data of sewage treatment plant
On, by building water outlet total phosphorus intelligent detecting method, propose that 5 classes and water outlet total phosphorus have the process variable of Close relation first,
And it specify that the particular location of each change measurement.In addition, intelligently counted by integrating hardware environment, communication channel, water outlet total phosphorus
The technologies such as Module-embedding are calculated, realize on-line intelligence detection and the real-time display of testing result of water outlet total phosphorus.
Background technology
The quick urbanization of eighties of last century and process of industrialization have triggered serious environmental pollution and shortage of resources problem.Its
Middle freshwater resources turn into global range to one of environment and resource focus of attention.The huge population base in China with rapidly
Industrialization development increasingly to increase the demand of freshwater resources, the water resource environment pollution problem thus triggered is also further tight
Weight, gradually threatens social life and national long-run development.With the attention of Environmental and Resources Management, at sewage
Reason has become the Main Means of sewage disposal and its recycling.In recent years, China actively builds sewage treatment facility, quickly
Promote city and the sewage treatment capacity of industrial scene.The issue of Environment Protect in China portion《China Environmental State Bulletin in 2014》
It has been shown that, by the end of the year 2014, the whole nation is accumulative to build up municipal sewage plant 6031, and the billion cubic meter of sewage treatment capacity about 1.8/
Day, treatment rate of domestic sewage reaches 90.2%.
For a long time, total phosphorus and its organic matter and inorganic content are always to influence domestic and international sewage treatment plant to go out in sewage
An important factor for water water quality.Sewage rich in phosphorus, which is discharged into rivers and lakes, easily causes eutrophication problem, causes water body animals and plants
Unbalance, heavy damage ecological environment is grown, many countries discharge the concentration of water outlet total phosphorus as sewage treatment plant in the world
One of core index of standard.However, the urban wastewater treatment firm that China has nearly 50% at present is unable to reach the phosphorus of national requirements
Discharge standard, this can not be obtained in real time mainly due to water outlet total phosphorus concentration, and water factory can not timely be adjusted to handling process
It is whole.At present, water outlet total phosphorus concentration mainly detects by the means of artificial sample and combination chemical experiment in sewage treatment plant.Chemistry side
Though method can guarantee that higher accuracy of detection, cumbersome, time-consuming (hour level), the real-time that can not meet increasingly to improve will
Ask, and easily cause secondary pollution.The in-line meter gradually risen in recent years can realize automatic data collection and the detection of water sample, save
The accidental error that manual operation may be brought is avoided while saving time (15~30 minutes), but it still uses chemism
Measurement, and purchase is very high with maintenance cost, most big-and-middle-sized water factories are powerless to undertake the in-line meter for configuring enough scales.Cause
This, how accurately, reliable and crucial water quality parameter is still sewage treatment industry face in measurement sewage disposal process at low cost
One of difficulty faced, it is extremely urgent to research and develop more advanced water outlet total phosphorus detection technique.
Found according to our researchs for many years and investigation, dirt can be realized using the soft-measuring technique based on neutral net
Water outlet total phosphorus is accurate in water treatment procedure, detects in real time, while can significantly save sewage treatment plant's cost, but is directed to both at home and abroad
The Intelligent Measurement of water outlet total phosphorus in sewage disposal process, not yet forms complete theoretical system, and the water outlet based on intelligent means is total
Phosphorus detecting system at home and abroad still belongs to blank.Therefore, the water outlet total phosphorus including software and hardware platform is built based on intelligent method
Intelligent checking system, filling up domestic and international technological gap and integrating sewage disposal industrial chain etc., have very high exploitation and
Application value.
The content of the invention
The present invention meets the hardware platform of the real-time detection demand of water outlet total phosphorus by configuring, and gets through logical between software and hardware
Path is interrogated, on the basis of Primary Study, further specify that the related process variable and its measurement position of water outlet total phosphorus.Together
When, by the real-time detection technique of sewage disposal water outlet total phosphorus of the Kernel-based methods data-driven of research, it is embedded in water outlet total phosphorus intelligence
Detecting system, software and hardware system are merged, complete a whole set of water outlet total phosphorus intelligent checking system.
The overall inventive architecture of water outlet total phosphorus intelligent checking system is as shown in Figure 1 in the present invention.The flow of system building is such as
Under：
It is special present invention firstly provides sewage disposal process water outlet total phosphorus in face of challenge caused by sewage treatment plant's big data
Modeling method is levied, from the actual demand of sewage disposal process, the dynamics of complexity is passed through into principal character argument table
State, based on sewage disposal process Analysis on Mechanism and data mining, obtain the process variable strong with water outlet total phosphorus correlation, and be based on
Neutral net completes the modeling to water outlet total phosphorus.On the analysis of total phosphorus formation mechenism in based on ASM1 models and BSM1 models
On the basis of, by gathering a large amount of actual sewage treatment plants data, based on partial least squares algorithm (PLS), analyze total phosphorus correlation
Sewage disposal process variable (PLS algorithms while considering how to summarize to greatest extent auxiliary variable spatial data information,
Consider explanation effect of the auxiliary variable to leading variable).Total phosphorus correlation sewage disposal process variable analysis process is mainly wrapped
Include：
Step 1：Independent variable collection is combined into X=[x1,...,xα], α is the auxiliary variable number that can be screened for, and dependent variable is denoted as
Y, and data are done into standardization.From X, principal component v and u is extracted respectively, it is necessary to meet to the greatest extent may be used in the matrix after y standardization
While information in respective data matrix can greatly be carried, its degree of correlation is maximum.Have
Wherein, V and U is respectively set X and y score matrix, and P and Q is respectively set X and y matrix of loadings, E and F
Respectively set X and y residual matrix.I=1,2 ..., α, α are the auxiliary variable number that can be screened for.vi,pi, uiWith qiPoint
Vector that Wei be in V, P, U and Q matrix.
Step 2：Principal component viWith uiCorrelation have,
ui=bivi, (3)
Wherein, biFor the coefficient correlation between two principal components, correlation matrix is denoted as b=[b1,b2,…,bα]T, α is
The auxiliary variable number that can be screened for.
Step 3：The termination condition of PLS algorithms is designated as,
Wherein, bselectTo have chosen the coefficient correlation of pivot number, RselectFor the validity for having chosen pivot of setting.
The validity can be determined by leaving-one method, | | | | it is norm computing.In the present invention, R is selectedselectFor 0.85.
Hardware platform is built, hardware platform main body includes pretreatment pool, preliminary sedimentation tank, anaerobic zone, anoxic zone, aerobic aeration area
With second pond, and diverse location lay measuring instrumentss, acquisition instrument composition including the pH detectors with thermometer, ORP examine
Survey instrument, DO measuring instruments, TSS measuring instruments, NH4- N and NO3- N measuring instruments；NH4- N and NO3- N only sets water side measurement point, test
Leaving water temperature T, the terminal oxidized reduction potential ORP in anaerobic zone, aerobic zone front end dissolved oxygen DO, aerobic zone end total solid suspend
Thing TSS and water outlet pH；The data above obtained from sewage disposal process is stored in instrument by translation interface, then passes through instrument
Background program runs real-time calling data storage in table；Water outlet total phosphorus content is predicted according to real time input data.
Brief description of the drawings
Fig. 1 is water outlet total phosphorus intelligent checking system integrated stand composition；
Fig. 2 is built for intelligent checking system hardware platform and the integrated stand composition of correlation variable's real-time acquiring technology；
Fig. 3 is water outlet total phosphorus TP correlation variable's Acquisition Instrument connection figures；
Fig. 4 is water outlet total phosphorus TP soft-sensor software frameworks；
Fig. 5 is water outlet total phosphorus intelligent checking system integrated support composition；
Fig. 6 is water outlet total phosphorus correlation variable's analysis result figure.
Embodiment
, can be with using Analysis on Mechanism and PLS algorithms when carrying out Variable Selection based on sewage treatment plant's True Data
Draw, each primary variables and water outlet total phosphorus correlation size are as shown in table 1:
The process variable strong with water outlet total phosphorus TP correlations of table 1
By site environment is limited, the measurement point position of each parameter it is more for sewage treatment process with the examining in demand such as supervising
Consider, and very high-frequency measurement need not be carried out in practical application, this can have an impact for the accuracy of data analysis.This
Outside, measured value fluctuation of the partial parameters (such as DO, ORP) in difference position is larger, and the difference of measurement point position may cause parameter
With the difference of water outlet total phosphorus correlation analysis result.Therefore, it is further analysis water outlet total phosphorus correlation variable, has built water outlet
Total phosphorus intelligent checking system hardware platform and correlation variable's real-time property obtain path, and global design framework is as shown in Figure 2.
When installing instrument, the parameter included first to table 1 is analyzed：1. PH, temperature the T variation in each flow are smaller,
Water side measurement point is only set；2. based on result early stage, NH4- N and NO3- N only sets water side measurement point, and main purpose is
Verify whether it is weaker with the relation of water outlet total phosphorus；3. COD and BOD wants to realize on-line measurement, it is necessary to configure correlate meter ten
Divide costliness, so as to which the cheap advantage of water outlet total phosphorus soft-measuring technique cost can be lost.Therefore, on-line checking is not carried out to it；④DO
Fluctuated with ORP in difference position measured value it is larger, therefore, need to analyze in further analysis its different Point Measurements whether
Analysis result can be had an impact.
Hardware platform is according to water outlet total phosphorus intelligent checking system functional requirement and A2/ O waste water processes design.Main body bag
Pretreatment pool, preliminary sedimentation tank, anaerobic zone, anoxic zone, aerobic aeration area and second pond are included, and measuring instrumentss are laid in diverse location,
The composition of acquisition instrument includes PH detectors (band thermometer T), ORP detectors, DO measuring instruments, TSS measuring instruments, NH4- N and NO3-
N measuring instruments.Specific connected mode is as shown in Figure 3：1-4 pops one's head in for part measuring instrumentss；5 represent probe and data acquisition unit
Between connecting interface；The 6 USB transmission line 7 between collector and PC is data acquisition unit, is put down in the hardware that the present invention is built
In platform 7 be WTW3430 display main frame；8 be computer, as the carrier and data receiver and processing platform of software, is also simultaneously
Display platform.
Correlation variable's data of instrument to collect are pre-processed, eliminate dependent variable data due to have random error,
The influence that dimension or order of magnitude difference are brought to total phosphorus Intelligent Measurement performance, by installing the group based on OPC standards in PC
State software, the data that hardware instrument to collect arrives are serviced into collection in real time to OPC client by OPC.Secondly, water outlet total phosphorus is passed through
Data in OPC client are read by the data distribution module in detecting system in real time, effective to complete correlation variable
The real-time acquisition of data, in order to preferably react sewage disposal process dynamic characteristic, the collection of auxiliary variable data keeps identical
Sampling instant and cycle.
Specific site setting is as shown in table 3, based on the result of PLS Algorithm Analysis, the strong water with water outlet total phosphorus TP correlations
Qualitative change amount includes：Leaving water temperature T, the terminal oxidized reduction potential ORP in anaerobic zone, aerobic zone front end dissolved oxygen DO, aerobic zone end
Total solid suspension TSS and water outlet PH, such as table 2.
Hardware platform is completed building, and after being verified to water outlet total phosphorus intelligent testing technology, the present invention uses software
Water outlet total phosphorus intelligent Computation Technology is encapsulated as functional module by the component technology in forward position in industry, strengthens durability, and water outlet is total
Phosphorus intelligent testing technology is integrated into complete water outlet total phosphorus intelligent checking system with the hardware and software platform built.
The present invention realizes each intermodule information transmission by establishing whole process system communication network.So that water outlet total phosphorus intelligence
Can detecting system can realize that data acquisition, data transfer, data storage and water outlet total phosphorus such as detect and shown in real time at the work(
Energy.Wherein, it is as shown in Figure 4 to the framework of the intelligent checking system software platform of water outlet total phosphorus.The function of mainly realizing includes：①
Water outlet total phosphorus correlation variable's data obtain in real time；2. water outlet total phosphorus soft-sensing model off-line training and emulation；3. water outlet total phosphorus
On-line prediction and result real-time display.
When integrating water outlet total phosphorus intelligent checking system, it is necessary first to information data is obtained from sewage disposal process, and will
Data are stored in instrument by translation interface, then run real-time calling data storage by background program in instrument.It is in addition, logical
Real-time detection and management of the form realization at interface to sewage disposal process are crossed, judges live water outlet total phosphorus concentration, and to total phosphorus
Change is fed back in time.Meanwhile according to the requirement of sewage disposal process realize data acquisition, data transfer, data storage, with
And the encapsulation of the module such as water outlet total phosphorus on-line checking, fault detect and the maintaining method of intelligent checking system are provided, passes through debugging
With the work for safeguarding guarantee detecting system normal table, Intelligent Measurement module predicts water outlet total phosphorus content according to real time input data
(such as Fig. 5).
Compared with sewage disposal hard measurement industry development present situation, the present invention has following innovation：
(1) correlation variable's analysis of key technical research of water outlet total phosphorus is carried out
The correlation process variable of water outlet total phosphorus content can be stated by being excavated using the methods of PLS, Analysis on Mechanism, first
By building water outlet total phosphorus intelligent checking system hardware platform, it is determined that 5 class correlation process variables and accurate each variable
Measurement point position.
(2) the real-time acquisition key technology research of correlation variable's data is carried out
The correlation variable's process data obtained in real time is subjected to time synchronized, the key that can not be obtained in real time for part
Variable data is acquired by increasing necessary equipment, it is ensured that the integrality and accuracy of data, and pass through Coordinated Communication mark
Standard simultaneously transfers data to host computer.
(3) water outlet total phosphorus intelligent checking system is integrated
Data acquisition, data transfer, data storage and water outlet total phosphorus intelligence are realized according to the requirement of sewage disposal process
The encapsulation of the modules such as detection, water outlet total phosphorus intelligent testing technology is integrated with the hardware and software platform built and developed, and completes water outlet
Total phosphorus intelligent checking system designs.
(1) specific implementation of the intelligent Computation Technology research of water outlet total phosphorus
When analyzing water outlet total phosphorus correlated variables, based on the water outlet total phosphorus intelligent checking system hardware platform independently built.Day
Treating capacity is 20 cubic metres, and it is sanitary sewage to enter water water source, using A2/ O techniques carry out sewage disposal, technological process specification, steady
It is fixed.
1. easily surveying process variable by the on-line checking instrument collection being placed in, the parameter of collection includes 9 kinds, parameter information
And collection position is as shown in table 2.
The process variable type that table 2 can be screened for
2. by data because abnormal data caused by the reasons such as gauge bias is rejected, with avoid bad data to point
Analysis result adversely affects.The partial data of collection is as shown in table 3.
The part of contaminated water treatment plant service data of table 3
3. being analyzed by PLS algorithms collection and reduced data, draw and strong auxiliary of water outlet total phosphorus correlation
Variable is helped, the input as follow-up neural network soft sensor model.The water outlet total phosphorus correlation variable analysis result such as institute of accompanying drawing 6
Show.Final choose includes：The terminal oxidized reduction potential ORP of temperature T, anaerobism, aerobic front end dissolved oxygen DO, aerobic end total solid
Auxiliary variable of the 5 class parameters as prediction water outlet total phosphorus including suspension TSS and water outlet PH.
(2) water outlet total phosphorus intelligent checking system design integrates with software and hardware function
Be embodied water outlet total phosphorus intelligent checking system it is integrated when, the present invention by trying platform and reality in the lab
The hardware platform for meeting water outlet total phosphorus intelligent checking system requirement is built in the sewage treatment plant of border, is treated with simulating actual sewage
Journey provides hardware environment and information data for intelligent checking system.Pass through the design and meter hardware and communication of intelligent testing technology
Design, water outlet total phosphorus intelligent testing technology is embedded in intelligent checking system, by information transfer by measurement result to foreground
Interface.
Claims (1)
1. the A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods, it is characterised in that step is as follows：
Step 1：Independent variable collection is combined into X=[x1,...,xα], α is the auxiliary variable number that can be screened for, and dependent variable is denoted as y, and
Data are done into standardization；From X, principal component v and u is extracted respectively, it is necessary to meet as big as possible in the matrix after y standardization
While ground carries information in respective data matrix, its degree of correlation is maximum；Have
<mrow>
<mi>X</mi>
<mo>=</mo>
<msup>
<mi>VP</mi>
<mi>T</mi>
</msup>
<mo>+</mo>
<mi>E</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>&alpha;</mi>
</munderover>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<msubsup>
<mi>p</mi>
<mi>i</mi>
<mi>T</mi>
</msubsup>
<mo>+</mo>
<mi>E</mi>
<mo>,</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>y</mi>
<mo>=</mo>
<msup>
<mi>UQ</mi>
<mi>T</mi>
</msup>
<mo>+</mo>
<mi>F</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>&alpha;</mi>
</munderover>
<msub>
<mi>u</mi>
<mi>i</mi>
</msub>
<msubsup>
<mi>q</mi>
<mi>i</mi>
<mi>T</mi>
</msubsup>
<mo>+</mo>
<mi>F</mi>
<mo>,</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, V and U is respectively set X and y score matrix, and P and Q is respectively set X and y matrix of loadings, and E is respectively with F
Set X and y residual matrix；I=1,2 ..., α, α are the auxiliary variable number that can be screened for；vi,pi,uiWith qiRespectively V,
Vector in P, U and Q matrix；
Step 2：Principal component viWith uiCorrelation have,
ui=bivi, (3)
<mrow>
<msub>
<mi>b</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<msubsup>
<mi>u</mi>
<mi>i</mi>
<mi>T</mi>
</msubsup>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>/</mo>
<msubsup>
<mi>v</mi>
<mi>i</mi>
<mi>T</mi>
</msubsup>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, biFor the coefficient correlation between two principal components, correlation matrix is denoted as b=[b1,b2,…,bα]T, α is to be available for
The auxiliary variable number of screening；
Step 3：The termination condition of PLS algorithms is designated as,
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>e</mi>
<mi>c</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>b</mi>
<mrow>
<mi>s</mi>
<mi>e</mi>
<mi>l</mi>
<mi>e</mi>
<mi>c</mi>
<mi>t</mi>
</mrow>
</msub>
<mo>|</mo>
<mo>|</mo>
</mrow>
<mrow>
<mo>|</mo>
<mo>|</mo>
<mi>b</mi>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
<mo>,</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, bselectTo have chosen the coefficient correlation of pivot number, | | | | it is norm computing；Selected RselectFor 0.85；
Hardware platform is built, hardware platform main body includes pretreatment pool, preliminary sedimentation tank, anaerobic zone, anoxic zone, aerobic aeration area and two
Heavy pond, and measuring instrumentss are laid in diverse location, the composition of acquisition instrument including the pH detectors with thermometer, ORP detectors,
DO measuring instruments, TSS measuring instruments, NH4- N and NO3- N measuring instruments；NH4- N and NO3- N only sets water side measurement point, tests water outlet
Temperature T, the terminal oxidized reduction potential ORP in anaerobic zone, aerobic zone front end dissolved oxygen DO, aerobic zone end total solid suspension TSS
And water outlet pH；The data above obtained from sewage disposal process is stored in instrument by translation interface, then by instrument
Background program runs real-time calling data storage；Water outlet total phosphorus content is predicted according to real time input data.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610237451.6A CN105675838B (en) | 2016-04-15 | 2016-04-15 | A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods |
| US15/206,702 US10788473B2 (en) | 2016-04-15 | 2016-07-11 | Computing system for detecting total phosphorus in effluent using data driven A2/O process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610237451.6A CN105675838B (en) | 2016-04-15 | 2016-04-15 | A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105675838A CN105675838A (en) | 2016-06-15 |
| CN105675838B true CN105675838B (en) | 2017-12-15 |
Family
ID=56310027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610237451.6A Active CN105675838B (en) | 2016-04-15 | 2016-04-15 | A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods |
Country Status (2)
| Country | Link |
|---|---|
| US (1) | US10788473B2 (en) |
| CN (1) | CN105675838B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106405030B (en) * | 2016-07-27 | 2018-07-24 | 北京北排科技有限公司 | A kind of water outlet total phosphorus detection device and detection method based on RBF neural |
| CN107664683A (en) * | 2016-07-30 | 2018-02-06 | 复凌科技（上海）有限公司 | A kind of water quality hard measurement Forecasting Methodology of total nitrogen |
| CN107664682A (en) * | 2016-07-30 | 2018-02-06 | 复凌科技（上海）有限公司 | A kind of water quality hard measurement Forecasting Methodology of ammonia nitrogen |
| CN106706491B (en) * | 2016-11-21 | 2024-01-23 | 北京工业大学 | Intelligent detection method for membrane bioreactor-MBR water permeability |
| CN106682316A (en) * | 2016-12-29 | 2017-05-17 | 北京工业大学 | Real-time effluent total-phosphorus monitoring system based on peak radial basis function neural network |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE509036C2 (en) * | 1993-06-29 | 1998-11-30 | Foss Tecator Ab | Procedure for measuring chemical and physical parameters to characterize and classify water suspensions |
| CN102313796B (en) * | 2011-05-27 | 2014-05-21 | 北京工业大学 | Soft measuring method of biochemical oxygen demand in sewage treatment |
| CA2842824C (en) * | 2011-07-26 | 2023-03-14 | General Electric Company | Wastewater treatment plant online monitoring and control |
| JP6214889B2 (en) * | 2013-03-14 | 2017-10-18 | 株式会社東芝 | Process monitoring and diagnosis device |
| CN103235096A (en) * | 2013-04-16 | 2013-08-07 | 广州铁路职业技术学院 | Sewage water quality detection method and apparatus |
| CN104376380B (en) * | 2014-11-17 | 2017-07-21 | 北京工业大学 | A kind of ammonia nitrogen concentration Forecasting Methodology based on recurrence self organizing neural network |
-
2016
- 2016-04-15 CN CN201610237451.6A patent/CN105675838B/en active Active
- 2016-07-11 US US15/206,702 patent/US10788473B2/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| US20170299565A1 (en) | 2017-10-19 |
| CN105675838A (en) | 2016-06-15 |
| US10788473B2 (en) | 2020-09-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105675838B (en) | A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods | |
| Zhou et al. | Industrial structural upgrading and spatial optimization based on water environment carrying capacity | |
| CN112001610B (en) | Agricultural non-point source pollution treatment method and device | |
| CN109133351A (en) | Membrane bioreactor-MBR fouling membrane intelligent early-warning method | |
| CN100514060C (en) | On-line virtual monitoring method for water chemical oxygen demand | |
| CN104636627A (en) | Soil heavy metal ecologic risk evaluation method | |
| CN111562242A (en) | Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system | |
| CN105445431A (en) | Urban surface water quality analysis method | |
| CN112070393A (en) | Wastewater quality detection system that industry and agriculture production discharged | |
| CN110889196B (en) | Water environment bearing capacity assessment method and device based on water quality model and storage medium | |
| CN103149166A (en) | Dual-wavelength ultraviolet method organic wastewater chemical oxygen demand (COD) detection device and method | |
| CN110019604A (en) | A kind of groundwater monitoring early warning system | |
| CN106405030B (en) | A kind of water outlet total phosphorus detection device and detection method based on RBF neural | |
| CN110070220A (en) | A kind of ammonia nitrogen index flexible measurement method based on neural network algorithm | |
| CN115327065A (en) | Hydraulic and hydroelectric engineering sample detection method and system | |
| CN107247888A (en) | Sewage disposal water outlet total phosphorus TP flexible measurement methods based on reserve pool network | |
| CN114858207A (en) | Soft measurement-based gridding source tracing investigation method for drain outlet of river channel | |
| CN106706491B (en) | Intelligent detection method for membrane bioreactor-MBR water permeability | |
| Bertrand-Krajewski et al. | Towards a better knowledge and management of infiltration and exfiltration in sewer systems: the APUSS project | |
| CN104569340B (en) | Underground environment quality determination method and device | |
| Sarminingsih et al. | Water quality monitoring system for temperature, pH, Turbidity, DO, BOD, and COD parameters based on internet of things in the garang watershed | |
| CN112630202A (en) | Method for identifying source of overflowing sewage in rainy days of urban drainage system | |
| CN106021884A (en) | Neural network principle-based method for predicting effluent concentration of subsurface flow wetland | |
| CN109580519A (en) | A kind of surface water COD on-line monitoring system and method based on ELM algorithm | |
| CN110988286B (en) | Intelligent water resource long-term detection system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |